There is a ton of information in the TIGER Census files at the U.S. Gov Census site. Unfortunately, it is not easily mapped to geolocations. I had to get the tract level shapefiles and then transform the variables in the … Read More

I noticed a question on the Analytics X Prize forum about how to determine the zip code for homicides with latitude and longitude values. While there are a plethora of online tools (Google Maps, etc) that will do this for … Read More

For my second attempt at predicting homicides in Philadelphia, I included roads in the model. I got the roads data from the census link in the last post, imported the roads into my PostgreSQL/PostGIS database, and visualized the resulting prediction … Read More

The Analytics X Prize evaluates entries by comparing the RMSE of the predicted proportion of homicides per zip code versus the actual proportion of homicides per zip code. RMSE is a standard way of comparing the predictive quality of models … Read More

The Analytics X Prize seeks to reproduce what Netflix did for movie recommendation prediction to crime prediction. The goal is to predict the proportion of homicides in each of the 47 zip codes in metropolitan Philadelphia. This kind of prediction … Read More